15 citations · 26 across the 5 of their papers we have counts for
6 papers · 1 filter
Deep Learning Approaches for Image Retrieval and Pattern Spotting in Ancient Documents
Kelly Lais Wiggers, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich +2
This paper describes two approaches for content-based image retrieval and pattern spotting in document images using deep learning. The first approach uses a pre-trained CNN model t…
Image Retrieval and Pattern Spotting using Siamese Neural Network
Kelly L. Wiggers, Alceu S. Britto, Laurent Heutte +2
This paper presents a novel approach for image retrieval and pattern spotting in document image collections. The manual feature engineering is avoided by learning a similarity-base…
Pattern Spotting in Historical Documents Using Convolutional Models
Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas +2
Pattern spotting consists of searching in a collection of historical document images for occurrences of a graphical object using an image query. Contrary to object detection, no pr…
Dynamic voting in multi-view learning for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Cancer diagnosis and treatment often require a personalized analysis for each patient nowadays, due to the heterogeneity among the different types of tumor and among patients. Radi…
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology I…
Dissimilarity-based representation for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Radiomics is a term which refers to the analysis of the large amount of quantitative tumor features extracted from medical images to find useful predictive, diagnostic or prognosti…